鄂西三峡地区雷电定位系统与卫星闪电观测数据的比较分析

Comparison of Lightning Location System Observation with Satallite Lightning Observation in Three Gorges Area Within Western Hubei

鄂西三峡地区是我国重要的输电线路走廊,雷击闪络事故比较严重。为研究这一地区雷电活动规律,对2005-2008年电网雷电定位系统(lightning location system,LLS)和卫星搭载的闪电图像传感器(lightning imagesensor,LIS)数据进行了配对比较研究。其中,以LIS数据为基准,在5ms时间误差范围内寻找LLS中与之配对的地闪数据,从2264个LIS闪电数据中成功配对出391组数据,配对数据平均地闪定位误差距离为0.114°(约11km),标准偏差为0.087,说明LIS和LLS数据对应性良好,具有很高的精度和平稳度。通过配对数据可以计算出鄂西三峡地区云闪与地闪比值Z1,其值大于通过传统平均闪电密度方法计算出的云闪与地闪比值Z0。同时,对比Prentice等人实测的云闪与地闪比值,则介于Z0和Z1之间。分析原因为,LIS对云层底部或高度较低处发生地闪的探测效率较低,导致计算结果差异。并且,通过配对数据还可以分析云闪与地闪比值Z1的时间、空间分布规律,发现鄂西三峡地区的Z1在2、5、9月有最大值(都>10),Z1空间分布与平均海拔高度相关系数为-0.33。研究表明,基于实时数据分析的雷电数据配对方法,能较好地反映雷暴的局部空间、时间规律。

In order to research the lightning activity regularity in Three gorges area,lightning location system（LLS） data in 2005~2008 years were matched with space flash observations of lightning image sensor（LIS） data.Based on LIS data,the paired LLS data were sought within 5 ms time interval.From the 2264 LIS lightning data,391 sets of data were successfully matched.The mean value of the positional error distance of matched data was 0.114°（about 11 km）,and the standard deviation was 0.087,fully demonstrating that the LIS data and the LLS data corresponded well,and had a high degree of accuracy and consistency.The inter-cloud（IC） and cloud-to-ground（CG） lightning ratio Z1 could be calculated by matched data,which was higher than Z0 calculated through the traditional mean flash density data.Then,the value of actual measurements by Prentice was between Z0 and Z1,because a poor CG detection efficiency of LIS on the bottom of clouds or low altitude resulted in differences in calculation results.The matching data also could be used to analyze the temporal and spatial distribution of IC and CG lightning ratio Z1,and it could be found that the maximum values of Z1 exceeded 10 in February,May and September.The related coefficient of Z1 with average altitude was-0.33.Studies show that the lightning data-matching method based on real-time data analysis could better reflect the local temporal and spatial law of thunderstorms.